DOE Optimization Suggestions

DC
I have a little background with Soldering. What constitutes a failure in your process? Do you have any physical attributes such as solder thickness that can be correlated to a failure?
 

DC,
If you can get the sample size up a bit, I think you can optimize using Binary Logistic Regression analysis. You can think of it as moving from 0/1 that you’re seeing now, to analyzing the probability of having a defect, from 0 to 100%.  I think you can stay with the CCD (Central Composite Design) for the response surface design, but the analysis will be a bit more involved.  You can email me if you’d like some help with trying this approach for the first time: [email protected] .
Best regards,Eric Maass

Robert:  Exactly right.  Too often I encounter folks stuck in a binary (discrete) world – yes/no, good/bad.  Even when there is an underlying measurement on a continuous scale, they want to compare this to an acceptance level and bin it as good/bad.
I have not yet encountered a situation where I couldn’t convert some discrete metric to a continuous one.  I had a challenge once on visual appeal of a product, but we were even able to do that via a judge panel with 1-100 scale ratings.
Think about what the customer finds important – often it is time to complete a task correctly.  If you cannot find another usable continuous measure, that is usually a viable measure.

DC
Robert Butler gave some great advice as usual on the DOE. So I’m going to go in a little bit different direction.
Have you tried to recreate the failure of “Splashes”. Often times we get so caught up in reducing variation and defects that we miss the true root cause of the problem or the fact that one of the variables we chose not use in the DOE really has significance when all other variables are “Optimized”.  Not really an answer to your question, but hope it helps .
 
Good Luck
PS: I had a similar issue with solder links and found that humidity was building in the enclosed fixture housing and “mini explosions” would create havoc on the links. Fix: we added silica desicant bags in the base of the fixture box and added some high flow are exchangers to the already Air Conditioned room with desicant dryers.

No. You always protect the customer first. EVOP is just a DOE strategy that says I make small changes
systematically and run each level of the experiment for a long time.
The implication of this that all involved in the process have to knowledgeable of what is being done and why. You also have a
higher responsibility to keep all involved in the result as well. If
you need some reference material on this let me know. I cannot
get to it immediately, but I will get to it.Chad’s suggestion is worth pursuing. Soldering is just physics, go
understand the physical phenomenon that is behind splashes. It
has to be minor explosions if you will of water or some kind of
residue chemical. I’d look to the cleaning and handling of the
boards prior to soldering.

  I don’t see that there is much of a debate.  My impression of your earlier posts was that you had run some designs, you had chosen the metric of yes/no defects as the output measure, you had found for the early work that this measure was acceptable, you were contemplating building a design using the critical variables identified in the earlier work and you were concerned that yes/no measures would be such (too many 0’s not enough 1’s) that the time/effort needed to run your new design (i.e. your EVOP) would be excessive.
  To that end I offered the thought that it might be worth changing the measure to time or mean time to events and use that to further refine the process.  I didn’t mean to imply you should try some kind of WGP (Wonder-Guess-Putter) approach using this measure just to see if you could luck into some kind of optimum.
  You could run the binary but you would still have to have a lot of data for this to work and at the end you would have odds ratios which aren’t the same thing as coefficients in a regression equation.  They will tell you that you chances of something occuring are greater or less depending on what you do (i.e. 4 times more likely to happen if A is at a high setting as opposed to A at a low setting) but given what I think you want from your analysis I don’t think this would be the best choice.
  The other thing to consider is this – you could be chasing a chimera – there is, of course, a chance that you will find a combination of factors that result in zero solder splashes but in my experience it is far more likely that you efforts will result in identifying a combination of factors that will significantly reduce, but not completely eliminate, solder splash.